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Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/15180
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dc.contributor.authorMuhammad Firdaus Shaarien_US
dc.contributor.authorIsmail Musirinen_US
dc.contributor.authorMuhamad Faliq Mohamad Nazeren_US
dc.contributor.authorShahrizal Jelanien_US
dc.contributor.authorFarah Adilah Jamaludinen_US
dc.contributor.authorMohd Helmi Mansoren_US
dc.contributor.authorA.V.Senthil Kumaren_US
dc.date.accessioned2020-08-25T04:45:21Z-
dc.date.available2020-08-25T04:45:21Z-
dc.date.issued2020-03-
dc.identifier.urihttp://dspace.uniten.edu.my/jspui/handle/123456789/15180-
dc.description.abstractInstalling DG in network system, has supported the distribution system to provide the increasing number of consumer demand and load, in order to achieve that this paper presents an efficient and fast converging optimization technique based on a modification of traditional evolutionary programming method for obtain the finest optimal location and power loss in distribution systems. The proposed algorithm that is supervised evolutionary programming is implemented in MATLAB and apply on the 69-bus feeder system in order to minimize the system power loss and obtaining the best optimal location of the distributed generators.en_US
dc.language.isoenen_US
dc.relation.ispartofIAES International Journal of Artificial Intelligence (IJ-AI)en_US
dc.titleSupervised evolutionary programming based technique for multi-DG installation in distribution systemen_US
dc.typeArticleen_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
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